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from app_settings import AppSettings
from utils import show_system_info
from PIL import Image
from backend.models.lcmdiffusion_setting import DiffusionTask
import constants
from argparse import ArgumentParser
from constants import APP_VERSION, LCM_DEFAULT_MODEL_OPENVINO
from models.interface_types import InterfaceType
from constants import DEVICE
from state import get_settings, get_context
parser = ArgumentParser(description=f"FAST SD CPU {constants.APP_VERSION}")
parser.add_argument(
"-s",
"--share",
action="store_true",
help="Create sharable link(Web UI)",
required=False,
)
group = parser.add_mutually_exclusive_group(required=False)
group.add_argument(
"-g",
"--gui",
action="store_true",
help="Start desktop GUI",
)
group.add_argument(
"-w",
"--webui",
action="store_true",
help="Start Web UI",
)
group.add_argument(
"-r",
"--realtime",
action="store_true",
help="Start realtime inference UI(experimental)",
)
group.add_argument(
"-v",
"--version",
action="store_true",
help="Version",
)
parser.add_argument(
"--lcm_model_id",
type=str,
help="Model ID or path,Default SimianLuo/LCM_Dreamshaper_v7",
default="SimianLuo/LCM_Dreamshaper_v7",
)
parser.add_argument(
"--prompt",
type=str,
help="Describe the image you want to generate",
)
parser.add_argument(
"--image_height",
type=int,
help="Height of the image",
default=512,
)
parser.add_argument(
"--image_width",
type=int,
help="Width of the image",
default=512,
)
parser.add_argument(
"--inference_steps",
type=int,
help="Number of steps,default : 4",
default=4,
)
parser.add_argument(
"--guidance_scale",
type=int,
help="Guidance scale,default : 1.0",
default=1.0,
)
parser.add_argument(
"--number_of_images",
type=int,
help="Number of images to generate ,default : 1",
default=1,
)
parser.add_argument(
"--seed",
type=int,
help="Seed,default : -1 (disabled) ",
default=-1,
)
parser.add_argument(
"--use_openvino",
action="store_true",
help="Use OpenVINO model",
)
parser.add_argument(
"--use_offline_model",
action="store_true",
help="Use offline model",
)
parser.add_argument(
"--use_safety_checker",
action="store_false",
help="Use safety checker",
)
parser.add_argument(
"--use_lcm_lora",
action="store_true",
help="Use LCM-LoRA",
)
parser.add_argument(
"--base_model_id",
type=str,
help="LCM LoRA base model ID,Default Lykon/dreamshaper-8",
default="Lykon/dreamshaper-8",
)
parser.add_argument(
"--lcm_lora_id",
type=str,
help="LCM LoRA model ID,Default latent-consistency/lcm-lora-sdv1-5",
default="latent-consistency/lcm-lora-sdv1-5",
)
parser.add_argument(
"-i",
"--interactive",
action="store_true",
help="Interactive CLI mode",
)
parser.add_argument(
"-t",
"--use_tiny_auto_encoder",
action="store_true",
help="Use tiny auto encoder for SD (TAESD)",
)
parser.add_argument(
"-f",
"--file",
type=str,
help="Input image for img2img mode",
default="",
)
parser.add_argument(
"--img2img",
action="store_true",
help="img2img mode; requires input file via -f argument",
)
args = parser.parse_args()
if args.version:
print(APP_VERSION)
exit()
# parser.print_help()
show_system_info()
print(f"Using device : {constants.DEVICE}")
if args.webui:
app_settings = get_settings()
else:
app_settings = get_settings()
print(f"Found {len(app_settings.lcm_models)} LCM models in config/lcm-models.txt")
print(
f"Found {len(app_settings.stable_diffsuion_models)} stable diffusion models in config/stable-diffusion-models.txt"
)
print(
f"Found {len(app_settings.lcm_lora_models)} LCM-LoRA models in config/lcm-lora-models.txt"
)
print(
f"Found {len(app_settings.openvino_lcm_models)} OpenVINO LCM models in config/openvino-lcm-models.txt"
)
if args.gui:
from frontend.gui.ui import start_gui
print("Starting desktop GUI mode(Qt)")
start_gui(
[],
app_settings,
)
elif args.webui:
from frontend.webui.ui import start_webui
print("Starting web UI mode")
start_webui(
args.share,
)
elif args.realtime:
from frontend.webui.realtime_ui import start_realtime_text_to_image
print("Starting realtime text to image(EXPERIMENTAL)")
start_realtime_text_to_image(args.share)
from frontend.webui.hf_demo import start_demo_text_to_image
print("Starting demo text to image")
start_demo_text_to_image(False)
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